Multi-objective optimal planning of EV charging stations and renewable energy resources for smart microgrids
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Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2022-12-26
Major/Subject
Mcode
Degree programme
Language
en
Pages
17
Series
Energy Science and Engineering
Abstract
Distribution system planners and operators have increasingly exposed great attention to maximizing the penetration of renewable energy resources (RERs), and electric vehicles (EVs) toward modern microgrids. Accordingly, intensive operational and economic problems are expected in such microgrids. Specifically, the operators need to meet the increased demand for EVs and increase the dependence on RERs. The charging strategy for EVs and the RER penetration level may result in increased power loss, thermal loading, voltage deviation, and overall system cost. To address these concerns, this paper proposed an optimal planning approach for allocating EV charging stations with controllable charging and hybrid RERs within multi-microgrids, where the charging strategy in the proposed planning approach contributed to improving power quality and overall system cost, where the voltage deviation, energy not supplied, total cost have been reduced to 26.03%, 49.57%, and 70.45%, respectively. The simulation results are compared with different optimization techniques to verify the effectiveness of the proposed algorithm. The proposed simultaneous allocation approach of EV charging stations and RERs can reduce operating costs for RERs and conventional stations while increasing the charging stations' capacity.Description
Publisher Copyright: © 2022 The Authors. Energy Science & Engineering published by Society of Chemical Industry and John Wiley & Sons Ltd.
Keywords
charging stations, electric vehicles, microgrids, optimization, renewable energy resources
Citation
Asaad , A , Ali , A , Mahmoud , K , Shaaban , M F , Lehtonen , M , Kassem , A M & Ebeed , M 2022 , ' Multi-objective optimal planning of EV charging stations and renewable energy resources for smart microgrids ' , Energy Science and Engineering . https://doi.org/10.1002/ese3.1385